Targeted discovery of quantitative trait loci for resistance to northern leaf blight and other diseases of maize

Recent advances in the population biology and management of maize foliar fungal pathogens Exserohilum turcicum, Cercospora zeina and Bipolaris maydis in Africa

Maize is the most widely cultivated and major security crop in sub-Saharan Africa. Three foliar diseases threaten maize production on the continent, namely northern leaf blight, gray leaf spot, and southern corn leaf blight. These are caused by the fungi Exserohilum turcicum, Cercospora zeina, and Bipolaris maydis, respectively. Yield losses of more than 10% can occur if these pathogens are diagnosed inaccurately or managed ineffectively. Here, we review recent advances in understanding the population biology and management of the three pathogens, which are present in Africa and thrive under similar environmental conditions during a single growing season. To effectively manage these pathogens, there is an increasing adoption of breeding for resistance at the small-scale level combined with cultural practices. Fungicide usage in African cropping systems is limited due to high costs and avoidance of chemical control. Currently, there is limited knowledge available on the population biology and genetics of these pathogens in Africa. The evolutionary potential of these pathogens to overcome host resistance has not been fully established. There is a need to conduct large-scale sampling of isolates to study their diversity and trace their migration patterns across the continent.

Exploring the Relationship Between Pattern-Triggered Immunity and Quantitative Resistance to Xanthomonas vasicola pv. vasculorum in Maize

Bacterial leaf streak (BLS) of maize is an emerging foliar disease of maize in the Americas. It is caused by the gram-negative nonvascular bacterium Xanthomonas vasicola pv. vasculorum. There are no chemical controls available for BLS, and thus, host resistance is crucial for managing X. vasicola pv. vasculorum. The objective of this study was to examine the genetic determinants of resistance to X. vasicola pv. vasculorum in maize, as well as the relationship between other defense-related traits and BLS resistance. Specifically, we examined the correlations among BLS severity, severity for three fungal diseases, flg-22 response, hypersensitive response, and auricle color. We conducted quantitative trait locus (QTL) mapping for X. vasicola pv. vasculorum resistance using the maize recombinant inbred line population Z003 (B73 × CML228). We detected three QTLs for BLS resistance. In addition to the disease resistance QTL, we detected a single QTL for auricle color. We observed significant, yet weak, correlations among BLS severity, levels of pattern-triggered immunity response and leaf flecking. These results will be useful for understanding resistance to X. vasicola pv. vasculorum and mitigating the impact of BLS on maize yields.

Integrated IBD Analysis, GWAS Analysis and Transcriptome Analysis to Identify the Candidate Genes for White Spot Disease in Maize

Foundation parents (FPs) play an irreplaceable role in maize breeding practices. Maize white spot (MWS) is an important disease in Southwest China that always seriously reduces production. However, knowledge about the genetic mechanism of MWS resistance is limited. In this paper, a panel of 143 elite lines were collected and genotyped by using the MaizeSNP50 chip with approximately 60,000 single nucleotide polymorphisms (SNPs) and evaluated for resistance to MWS among 3 environments, and a genome-wide association study (GWAS) and transcriptome analysis were integrated to reveal the function of the identity-by-descent (IBD) segments for MWS. The results showed that (1) 225 IBD segments were identified only in the FP QB512, 192 were found only in the FP QR273 and 197 were found only in the FP HCL645. (2) The GWAS results showed that 15 common quantitative trait nucleotides (QTNs) were associated with MWS. Interestingly, SYN10137 and PZA00131.14 were in the IBD segments of QB512, and the SYN10137-PZA00131.14 region existed in more than 58% of QR273's descendants. (3) By integrating the GWAS and transcriptome analysis, Zm00001d031875 was found to located in the region of SYN10137-PZA00131.14. These results provide some new insights for the detection of MWS's genetic variation mechanisms.

Identification of Early and Extra-Early Maturing Tropical Maize Inbred Lines with Multiple Disease Resistance for Enhanced Maize Production and Productivity in Sub-Saharan Africa

Maize, a staple for millions across sub-Saharan Africa (SSA), faces major biotic constraints affecting production and safety of the crop. These include northern corn leaf blight (NCLB), southern corn leaf blight (SCLB), Curvularia leaf spot (CLS), and aflatoxin contamination by Exserohilum turcicum, Bipolaris maydis, Curvularia lunata, and Aspergillus flavus, respectively. Farmers in SSA would benefit tremendously if high-yielding maize hybrids with multiple disease resistance (MDR) were developed and commercialized. In all, 49 early-maturing (EM; 90 to 95 days to physiological maturity) and 55 extra-early-maturing (EEM, 80 to 85 days to physiological maturity) inbred lines developed by the International Institute of Tropical Agriculture were identified as resistant to NCLB in field evaluations in multiple agroecologies of Nigeria in 2017 and 2018. From each maturity group, the 30 most resistant inbreds were selected for evaluation for resistance to SCLB and CLS using a detached-leaf assay. Additionally, the inbreds were screened for resistance to kernel rot and aflatoxin contamination using a kernel screening assay. In all, 7 EM and 6 EEM maize inbreds were found to be highly resistant to the three foliar pathogens while 10 inbreds were resistant to the foliar pathogens and supported significantly less (P = 0.01) aflatoxin accumulation than other inbreds. Inbreds having MDR should be tested extensively in hybrid combinations and commercialized. Large-scale use of maize hybrids with MDR would (i) increase maize production and productivity and (ii) reduce losses caused by aflatoxin contamination. Overall, planting of EM and EEM maize hybrids with MDR would contribute to food security, reduced aflatoxin exposure, and increased incomes of maize farmers in SSA.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Molecular Genetics of Anthracnose Resistance in Maize

Maize (Zea mays), also called corn, is one of the top three staple food crops worldwide and is also utilized as feed (e.g., feed grain and silage) and a source of biofuel (e.g., bioethanol). Maize production is hampered by a myriad of factors, including although not limited to fungal diseases, which reduce grain yield and downgrade kernel quality. One such disease is anthracnose leaf blight and stalk rot (ALB and ASR) caused by the hemibiotrophic fungal pathogen Colletotrichum graminicola. The pathogen deploys a biphasic infection strategy to colonize susceptible maize genotypes, comprising latent (symptomless) biotrophic and destructive (symptomatic) necrotrophic phases. However, the resistant maize genotypes restrict the C. graminicola infection and in planta fungal proliferation during the biotrophic phase of the infection. Some studies on the inheritance of ASR resistance in the populations derived from biparental resistant and susceptible genotypes reveal that anthracnose is likely a gene-for-gene disease in which the resistant maize genotypes and C. graminicola recognize each other by their matching pairs of nucleotide-binding leucine-rich repeat resistance (NLR) proteins (whose coding genes are localized in disease QTL) and effectors (1–2 effectors/NLR) during the biotrophic phase of infection. The Z. mays genome encodes approximately 144 NLRs, two of which, RCg1 and RCg1b, located on chromosome 4, were cloned and functionally validated for their role in ASR resistance. Here, we discuss the genetic architecture of anthracnose resistance in the resistant maize genotypes, i.e., disease QTL and underlying resistance genes. In addition, this review also highlights the disease cycle of C. graminicola and molecular factors (e.g., virulence/pathogenicity factors such as effectors and secondary metabolites) that contribute to the pathogen’s virulence on maize. A detailed understanding of molecular genetics underlying the maize—C. graminicola interaction will help devise effective management strategies against ALB and ASR.

Mapping and Validation of Major Quantitative Trait Loci for Resistance to Northern Corn Leaf Blight Along With the Determination of the Relationship Between Resistances to Multiple Foliar Pathogens of Maize (Zea mays L.)

Among various foliar diseases affecting maize yields worldwide, northern corn leaf blight (NCLB) is economically important. The genetics of resistance was worked out to be quantitative in nature thereby suggesting the need for the detection of quantitative trait loci (QTL) to initiate effective marker-aided breeding strategies. From the cross CML153 (susceptible) × SKV50 (resistant), 344 F_{2 : 3} progenies were derived and screened for their reaction to NCLB during the rainy season of 2013 and 2014. The identification of QTL affecting resistance to NCLB was carried out using the genetic linkage map constructed with 194 polymorphic SNPs and the disease data recorded on F_{2 : 3} progeny families. Three QTL for NCLB resistance were detected on chromosomes 2, 5, and 8 with the QTL qNCLB-8-2 explaining the highest phenotypic variation of 16.34% followed by qNCLB-5 with 10.24%. QTL for resistance to sorghum downy mildew (SDM) and southern corn rust (SCR) were also identified from one season phenotypic data, and the co-location of QTL for resistance to three foliar diseases was investigated. QTL present in chromosome bins 8.03, 5.03, 5.04, and 3.04 for resistance to NCLB, SDM, and SCR were co-localized, indicating their usefulness for the pyramiding of quantitative resistance to multiple foliar pathogens. Marker-assisted selection was practiced in the crosses CM212 × SKV50, HKI162 × SKV50, and CML153 × SKV50 employing markers linked to major QTL on chromosomes 8, 2, and 10 for NCLB, SDM, and SCR resistance, respectively. The populations were advanced to F₆ stage to derive multiple disease-resistant inbred lines. Out of the 125 lines developed, 77 lines were tested for their combining ability and 39 inbred lines exhibited high general combining ability with an acceptable level of resistance to major diseases.

Genetic Dissection of Resistance to Gray Leaf Spot by Combining Genome-Wide Association, Linkage Mapping, and Genomic Prediction in Tropical Maize Germplasm

Gray leaf spot (GLS) is one of the major maize foliar diseases in sub-Saharan Africa. Resistance to GLS is controlled by multiple genes with additive effect and is influenced by both genotype and environment. The objectives of the study were to dissect the genetic architecture of GLS resistance through linkage mapping and genome-wide association study (GWAS) and assessing the potential of genomic prediction (GP). We used both biparental populations and an association mapping panel of 410 diverse tropical/subtropical inbred lines that were genotyped using genotype by sequencing. Phenotypic evaluation in two to four environments revealed significant genotypic variation and moderate to high heritability estimates ranging from 0.43 to 0.69. GLS was negatively and significantly correlated with grain yield, anthesis date, and plant height. Linkage mapping in five populations revealed 22 quantitative trait loci (QTLs) for GLS resistance. A QTL on chromosome 7 (qGLS7-105) is a major-effect QTL that explained 28.2% of phenotypic variance. Together, all the detected QTLs explained 10.50, 49.70, 23.67, 18.05, and 28.71% of phenotypic variance in doubled haploid (DH) populations 1, 2, 3, and F3 populations 4 and 5, respectively. Joint linkage association mapping across three DH populations detected 14 QTLs that individually explained 0.10-15.7% of phenotypic variance. GWAS revealed 10 significantly (p < 9.5 × 10-6) associated SNPs distributed on chromosomes 1, 2, 6, 7, and 8, which individually explained 6-8% of phenotypic variance. A set of nine candidate genes co-located or in physical proximity to the significant SNPs with roles in plant defense against pathogens were identified. GP revealed low to moderate prediction correlations of 0.39, 0.37, 0.56, 0.30, 0.29, and 0.38 for within IMAS association panel, DH pop1, DH pop2, DH pop3, F3 pop4, and F3 po5, respectively, and accuracy was increased substantially to 0.84 for prediction across three DH populations. When the diversity panel was used as training set to predict the accuracy of GLS resistance in biparental population, there was 20-50% reduction compared to prediction within populations. Overall, the study revealed that resistance to GLS is quantitative in nature and is controlled by many loci with a few major and many minor effects. The SNPs/QTLs identified by GWAS and linkage mapping can be potential targets in improving GLS resistance in breeding programs, while GP further consolidates the development of high GLS-resistant lines by incorporating most of the major- and minor-effect genes.

Maize Introgression Library Provides Evidence for the Involvement of liguleless1 in Resistance to Northern Leaf Blight

Plant disease resistance is largely governed by complex genetic architecture. In maize, few disease resistance loci have been characterized. Near-isogenic lines are a powerful genetic tool to dissect quantitative trait loci. We analyzed an introgression library of maize (Zea mays) near-isogenic lines, termed a nested near-isogenic line library for resistance to northern leaf blight caused by the fungal pathogen Setosphaeria turcica The population was comprised of 412 BC₅F₄ near-isogenic lines that originated from 18 diverse donor parents and a common recurrent parent, B73. Single nucleotide polymorphisms identified through genotyping by sequencing were used to define introgressions and for association analysis. Near-isogenic lines that conferred resistance and susceptibility to northern leaf blight were comprised of introgressions that overlapped known northern leaf blight quantitative trait loci. Genome-wide association analysis and stepwise regression further resolved five quantitative trait loci regions, and implicated several candidate genes, including Liguleless1, a key determinant of leaf architecture in cereals. Two independently-derived mutant alleles of liguleless1 inoculated with S. turcica showed enhanced susceptibility to northern leaf blight. In the maize nested association mapping population, leaf angle was positively correlated with resistance to northern leaf blight in five recombinant inbred line populations, and negatively correlated with northern leaf blight in four recombinant inbred line populations. This study demonstrates the power of an introgression library combined with high density marker coverage to resolve quantitative trait loci. Furthermore, the role of liguleless1 in leaf architecture and in resistance to northern leaf blight has important applications in crop improvement.

Identification of Loci That Confer Resistance to Bacterial and Fungal Diseases of Maize

Crops are hosts to numerous plant pathogenic microorganisms. Maize has several major disease issues; thus, breeding multiple disease resistant (MDR) varieties is critical. While the genetic basis of resistance to multiple fungal pathogens has been studied in maize, less is known about the relationship between fungal and bacterial resistance. In this study, we evaluated a disease resistance introgression line (DRIL) population for the foliar disease Goss’s bacterial wilt and blight (GW) and conducted quantitative trait locus (QTL) mapping. We identified a total of ten QTL across multiple environments. We then combined our GW data with data on four additional foliar diseases (northern corn leaf blight, southern corn leaf blight, gray leaf spot, and bacterial leaf streak) and conducted multivariate analysis to identify regions conferring resistance to multiple diseases. We identified 20 chromosomal bins with putative multiple disease effects. We examined the five chromosomal regions (bins 1.05, 3.04, 4.06, 8.03, and 9.02) with the strongest statistical support. By examining how each haplotype effected each disease, we identified several regions associated with increased resistance to multiple diseases and three regions associated with opposite effects for bacterial and fungal diseases. In summary, we identified several promising candidate regions for multiple disease resistance in maize and specific DRILs to expedite interrogation.

Genetic mapping of quantitative trait loci and a major locus for resistance to grey leaf spot in maize

The genetic basis of GLS resistance was dissected using two DH populations sharing a common resistant parent. A major QTL repeatedly detected in multiple developmental stages and environments was fine mapped in a backcross population. Grey leaf spot (GLS), caused by Cercospora zeae-maydis or Cercospora zeina, is a highly destructive foliar disease worldwide. However, the mechanism of resistance against GLS is not well understood. To study the inheritance of this resistance, we developed two doubled haploid (DH) populations sharing a common resistant parent. The two DH populations were grown in two locations representing the typical maize-growing mountain area in Southwest China for 2 years. GLS disease severity was investigated 2 or 3 times until maturity in the 2 years, and the area under the disease progress curve was calculated. Two high-density linkage maps were constructed by genotyping-by-sequencing. A total of 22 quantitative trait loci (QTLs) were detected for GLS resistance, with most QTLs being repeatedly detected in different stages, locations and years. The confidence intervals of two major QTLs (qGLS_Y2-2 and qGLS_Z2-1) on chromosome 2 from the two DH populations overlapped with each other and were integrated into one consensus QTL (qGLS_YZ2-1). Using highly resistant and highly susceptible plants from a BC₃ population, we fine mapped this genetic locus to a genomic region of 2.4 Mb. Using a panel of 255 inbred lines from breeding programmes, we detected associations between markers in the qGLS_YZ2-1 region and GLS resistance. The peak marker (ID-B1) will be very useful for marker-assisted breeding for GLS resistance.

Conserved defense responses between maize and sorghum to Exserohilum turcicum

BACKGROUND

Exserohilum turcicum is an important pathogen of both sorghum and maize, causing sorghum leaf blight and northern corn leaf blight. Because the same pathogen can infect and cause major losses for two of the most important grain crops, it is an ideal pathosystem to study plant-pathogen evolution and investigate shared resistance mechanisms between the two plant species. To identify sorghum genes involved in the E. turcicum response, we conducted a genome-wide association study (GWAS).

RESULTS

Using the sorghum conversion panel evaluated across three environments, we identified a total of 216 significant markers. Based on physical linkage with the significant markers, we detected a total of 113 unique candidate genes, some with known roles in plant defense. Also, we compared maize genes known to play a role in resistance to E. turcicum with the association mapping results and found evidence of genes conferring resistance in both crops, providing evidence of shared resistance between maize and sorghum.

CONCLUSIONS

Using a genetics approach, we identified shared genetic regions conferring resistance to E. turcicum in both maize and sorghum. We identified several promising candidate genes for resistance to leaf blight in sorghum, including genes related to R-gene mediated resistance. We present significant advancements in the understanding of host resistance to E. turcicum, which is crucial to reduce losses due to this important pathogen.

De novo Assembly of Transcriptomes From a B73 Maize Line Introgressed With a QTL for Resistance to Gray Leaf Spot Disease Reveals a Candidate Allele of a Lectin Receptor-Like Kinase

Gray leaf spot (GLS) disease in maize, caused by the fungus Cercospora zeina, is a threat to maize production globally. Understanding the molecular basis for quantitative resistance to GLS is therefore important for food security. We developed a de novo assembly pipeline to identify candidate maize resistance genes. Near-isogenic maize lines with and without a QTL for GLS resistance on chromosome 10 from inbred CML444 were produced in the inbred B73 background. The B73-QTL line showed a 20% reduction in GLS disease symptoms compared to B73 in the field (p = 0.01). B73-QTL leaf samples from this field experiment conducted under GLS disease pressure were RNA sequenced. The reads that did not map to the B73 or C. zeina genomes were expected to contain novel defense genes and were de novo assembled. A total of 141 protein-coding sequences with B73-like or plant annotations were identified from the B73-QTL plants exposed to C. zeina. To determine whether candidate gene expression was induced by C. zeina, the RNAseq reads from C. zeina-challenged and control leaves were mapped to a master assembly of all of the B73-QTL reads, and differential gene expression analysis was conducted. Combining results from both bioinformatics approaches led to the identification of a likely candidate gene, which was a novel allele of a lectin receptor-like kinase named L-RLK-CML that (i) was induced by C. zeina, (ii) was positioned in the QTL region, and (iii) had functional domains for pathogen perception and defense signal transduction. The 817AA L-RLK-CML protein had 53 amino acid differences from its 818AA counterpart in B73. A second "B73-like" allele of L-RLK was expressed at a low level in B73-QTL. Gene copy-specific RT-qPCR confirmed that the l-rlk-cml transcript was the major product induced four-fold by C. zeina. Several other expressed defense-related candidates were identified, including a wall-associated kinase, two glutathione s-transferases, a chitinase, a glucan beta-glucosidase, a plasmodesmata callose-binding protein, several other receptor-like kinases, and components of calcium signaling, vesicular trafficking, and ethylene biosynthesis. This work presents a bioinformatics protocol for gene discovery from de novo assembled transcriptomes and identifies candidate quantitative resistance genes.

Characterization and Molecular Mapping of Two Novel Genes Resistant to Pythium Stalk Rot in Maize

Pythium stalk rot caused by Pythium inflatum is becoming a more and more serious disease in maize, and it has caused severe yield loss in China in recent years. Deployment of resistant maize varieties is the most effective way to control this disease. Searching for the resistant maize germplasm and identifying the resistance genes are the vital processes in the breeding program. The maize inbred line X178 previously showed high resistance to Pythium stalk rot. Thus, this study aimed to reveal the gene(s) resistance to Pythium stalk rot in X178 by resistance inheritance analysis using the derived F₂ and F_2:3 genetic populations. The results showed that two independently inherited dominant genes, designated RpiX178-1 and RpiX178-2, carried by X178 are responsible for its resistance relative to the susceptible parent Ye107; they are located on regions of maize chromosome (chr.) 1 bin 1.09 and chr. 4 bin 4.08, respectively, and flanked by markers umc2047 and bnlg1671 as well as bnlg1444 and umc1313, respectively, by linkage analysis. Subsequently, RpiX178-1 was finely mapped between markers SSRZ8 and IDP2347, with genetic distances of 0.6 and 1.1 cM, respectively, and the physical distance of the target region was about 700 kb. RpiX178-2 was also further located between markers bnlg1444 and umc2041, with a genetic distance of 2.4 cM. Moreover, we confirmed that the two genes RpiX178-1 and RpiX178-2 were newly identified and different from those genes known on chrs. 1 and 4 according to results of allelism testing. Herein, we newly identified two genes resistant to P. inflatum, which provided important genetic information for resistance to Pythium stalk rot in maize.

Using Maize Chromosome Segment Substitution Line Populations for the Identification of Loci Associated with Multiple Disease Resistance

Southern Leaf Blight (SLB), Northern Leaf Blight (NLB), and Gray Leaf Spot (GLS) caused by Cochliobolus heterostrophus, Setosphaeria turcica, and Cercospora zeae-maydis respectively, are among the most important diseases of corn worldwide. Previously, moderately high and significantly positive genetic correlations between resistance levels to each of these diseases were identified in a panel of 253 diverse maize inbred lines. The goal of this study was to identify loci underlying disease resistance in some of the most multiple disease resistant (MDR) lines by the creation of chromosome segment substitution line (CSSL) populations in multiple disease susceptible (MDS) backgrounds. Four MDR lines (NC304, NC344, Ki3, NC262) were used as donor parents and two MDS lines (Oh7B, H100) were used as recurrent parents to produce eight BC3F4:5 CSSL populations comprising 1,611 lines in total. Each population was genotyped and assessed for each disease in replicated trials in two environments. Moderate to high heritabilities on an entry mean basis were observed (0.32 to 0.83). Several lines in each population were significantly more resistant than the MDS parental lines for each disease. Multiple quantitative trait loci (QTL) for disease resistance were detected for each disease in most of the populations. Seventeen QTL were associated with variation in resistance to more than one disease (SLB/NLB: 2; SLB/GLS: 7; NLB/GLS: 2 and 6 to all three diseases). For most populations and most disease combinations, significant correlations were observed between disease scores and also between marker effects for each disease. The number of lines that were resistant to more than one disease was significantly higher than would be expected by chance. Using the results from individual QTL analyses, a composite statistic based on Mahalanobis distance (Md) was used to identify joint marker associations with multiple diseases. Across all populations and diseases, 246 markers had significant Md values. However further analysis revealed that most of these associations were due to strong QTL effects on a single disease. Together, these findings reinforce our previous conclusions that loci associated with resistance to different diseases are clustered in the genome more often than would be expected by chance. Nevertheless true MDR loci which have significant effects on more than one disease are still much rarer than loci with single disease effects.

Increased experimental conditions and marker densities identified more genetic loci associated with southern and northern leaf blight resistance in maize

Southern leaf blight (SLB) and northern leaf blight (NLB) are the two major foliar diseases limiting maize production worldwide. Upon previous study with the nested association mapping (NAM) population, which consist of 5,000 recombinant inbred lines from 25 parents crossed with B73, we expanded the phenotyping environments from the United States (US) to China, and increased the marker densities from 1106 to 7386 SNPs for linkage mapping, and from 1.6 to 28.5 million markers for association mapping. We identified 49 SLB and 48 NLB resistance-related unique QTLs in linkage mapping, and multiple loci in association mapping with candidate genes involved in known plant disease-resistance pathways. Furthermore, an independent natural population with 282 diversified inbred lines were sequenced for four candidate genes selected based on their biological functions. Three of them demonstrated significant associations with disease resistance. These findings provided valuable resources for further implementations to develop varieties with superior resistance for NLB and SLB.

Intraspecific variation of residual heterozygosity and its utility for quantitative genetic studies in maize

BACKGROUND

Residual heterozygosity (RH) in advanced inbred lines of plants benefits quantitative trait locus (QTL) mapping studies. However, knowledge of factors affecting the genome-wide distribution of RH remains limited.

RESULTS

A set of 2196 heterogeneous inbred family (HIF) maize lines derived from 12 recombinant inbred line (RIL) populations was genotyped using the Maize50K SNP chip. A total of 18,615 unique RH intervals were identified, ranging from 505 to 2095 intervals per population, with average maize genome coverage of 94.8%. Across all populations, there were 8.6 RH intervals per HIF line on average, ranging from 1.8 to 14 intervals; the average size of an RH interval was approximately 58.7 Mb, ranging from 7.2 to 74.1 Mb. A given RH region was present in an average of 5 different individuals within a population. Seven RH hotspots, where RH segments were enriched in the genome, were found to be subject to selection during population development. The RH patterns varied significantly across populations, presumably reflecting differences in the genetic background of each population, and 8 QTLs were found to affect heterozygosity levels in the RH hotspots. The potential use of this HIF library for the fine mapping of QTLs was assessed based on publicly available QTL information, achieving a ≤ 1 Mb resolution on average.

CONCLUSION

The examined library of HIF lines offers insight into the RH landscape and its intraspecific variation and provides a useful resource for the QTL cloning of important agronomic traits in maize.

Navigating complexity to breed disease-resistant crops

Plant diseases are responsible for substantial crop losses each year and pose a threat to global food security and agricultural sustainability. Improving crop resistance to pathogens through breeding is an environmentally sound method for managing disease and minimizing these losses. However, it is challenging to breed varieties with resistance that is effective, stable and broad-spectrum. Recent advances in genetic and genomic technologies have contributed to a better understanding of the complexity of host-pathogen interactions and have identified some of the genes and mechanisms that underlie resistance. This new knowledge is benefiting crop improvement through better-informed breeding strategies that utilize diverse forms of resistance at different scales, from the genome of a single plant to the plant varieties deployed across a region.

Large-scale Maize Seedling Infection with Exserohilum turcicum in the Greenhouse

Northern corn leaf blight (NCLB) is a serious foliar disease of maize (Zea mays) worldwide and breeding for resistance is of primary importance for maize crop protection. Phenotyping for NCLB resistance is well established in the field, but such experiments depend on suitable environmental conditions and are seasonal. Here we describe a greenhouse seedling approach that is suitable for testing thousands of seedling plants in a single experiment with a duration of 37 days. Three scoring methods were used to quantify the disease severity: the area under the disease progress curve (AUDPC), the primary diseased leaf area of the inoculated leaves at 16 days post inoculation (PrimDLA at 16 dpi) and the incubation period (IP) that was determined as days from inoculation to symptom appearance. By testing a diverse panel of maize genotypes, a high correlation between the three different methods was observed (81.9% to 94.1%), indicating that each of scoring methods can be applied for disease quantification. Thus, the seedling assay developed served as a relatively simple and high-throughput method for phenotyping NCLB disease resistance under greenhouse condition.

Genetics of Resistance and Pathogenicity in the Maize/Setosphaeria turcica Pathosystem and Implications for Breeding

Northern corn leaf blight (NCLB), the most devastating leaf pathogen in maize (Zea mays L.), is caused by the heterothallic ascomycete Setosphaeria turcica. The pathogen population shows an extremely high genetic diversity in tropical and subtropical regions. Varietal resistance is the most efficient technique to control NCLB. Host resistance can be qualitative based on race-specific Ht genes or quantitative controlled by many genes with small effects. Quantitative resistance is moderately to highly effective and should be more durable combatting all races of the pathogen. Quantitative resistance must, however, be analyzed in many environments (= location × year combinations) to select stable resistances. In the tropical and subtropical environments, quantitative resistance is the preferred option to manage NCLB epidemics. Resistance level can be increased in practical breeding programs by several recurrent selection cycles based on disease severity rating and/or by genomic selection. This review aims to address two important aspects of the NCLB pathosystem: the genetics of the fungus S. turcica and the modes of inheritance of the host plant maize, including successful breeding strategies regarding NCLB resistance. Both drivers of this pathosystem, pathogen, and host, must be taken into account to result in more durable resistance.

Fine mapping of a quantitative resistance gene for gray leaf spot of maize (Zea mays L.) derived from teosinte (Z. mays ssp. parviglumis)

In this study we mapped the QTL Qgls8 for gray leaf spot (GLS) resistance in maize to a ~130 kb region on chromosome 8 including five predicted genes. In previous work, using near isogenic line (NIL) populations in which segments of the teosinte (Zea mays ssp. parviglumis) genome had been introgressed into the background of the maize line B73, we had identified a QTL on chromosome 8, here called Qgls8, for gray leaf spot (GLS) resistance. We identified alternate teosinte alleles at this QTL, one conferring increased GLS resistance and one increased susceptibility relative to the B73 allele. Using segregating populations derived from NIL parents carrying these contrasting alleles, we were able to delimit the QTL region to a ~130 kb (based on the B73 genome) which encompassed five predicted genes.

Identification and introgression of QTLs implicated in resistance to sorghum downy mildew (Peronosclerospora sorghi (Weston and Uppal) C. G. Shaw) in maize through marker-assisted selection

Sorghum downy mildew caused by Peronosclerospora sorghi is a major disease of maize and resistance is under the control of polygenes which necessitated identification of quantitative-trait loci (QTLs) for initiating marker-assisted introgression of resistant QTLs in elite susceptible inbred lines. In the present study, QTLs for sorghum downy mildew (SDM) resistance in maize were identified based on cosegregation with linked simple sequence repeats in 185 F2 progeny from a cross between susceptible (CM500-19) and resistant (MAI105) parents. F3 families were screened in the National Sorghum Downy Mildew Screening Nursery during 2010 and 2011. High heritability was observed for the disease reaction. The final map generated using 87 SSR markers had 10 linkage groups, spanning a length of 1210.3 cM. Although, we used only 87 SSR markers for mapping, the per cent of genome within 20 cM to the nearest marker was 88.5. Three putative QTLs for SDM resistance were located on chromosomes 3 (bin 3.01), 6 (bin 6.01) and 2 (bin 2.02) using composite interval mapping. The locus on chromosome 3 had a major effect and explained up to 12.6% of the phenotypic variation. The other two QTLs on chromosomes 6 and 2 had minor effects with phenotypic variation of 7.1 and 2%. The three QTLs appeared to have additive effects on resistance. The QTLs on chromosomes 3 and 6 were successfully used in the marker-assisted selection programme for introgression of resistance to SDM in eight susceptible maize lines.

Quantitative trait locus analysis and fine mapping of the qPL6 locus for panicle length in rice

Two QTLs were identified to control panicle length in rice backcross lines, and one QTL qPL6 was finely mapped with potential in high yield breeding. Panicle length (PL) is the key determinant of panicle architecture in rice, and strongly affects yield components, such as grain number per panicle. However, this trait has not been well studied genetically nor its contribution to yield improvement. In this study, we performed quantitative trait locus (QTL) analysis for PL in four backcross populations derived from the cross of Nipponbare (japonica) and WS3 (indica), a new plant type (NPT) variety. Two QTLs were identified on chromosome 6 and 8, designated as qPL6 and qPL8, respectively. Near-isogenic lines (NILs) were developed to evaluate their contribution to important agronomic traits. We found that qPL6 and qPL8 had additive effects on PL trait. For the qPL6 locus, the WS3 allele also increased panicle primary and secondary branches and grain number per panicle. Moreover, this allele conferred wide and strong culms, a character of lodging resistance. By analyzing key recombinants in two steps, the qPL6 locus was finely mapped to a 25-kb interval, and 3 candidate genes were identified. According to the single nucleotide polymorphisms (SNPs) within candidate genes, 5 dCaps markers were designed and used to get haplotypes of 96 modern Chinese varieties, which proved that qPL6 locus is differentiated between indica and temperate japonica varieties. Taken together, the superior qPL6 allele can be applied in rice breeding programs for large sink size, particularly for japonica varieties that originally lack the allele.

Resistance to gray leaf spot of maize: genetic architecture and mechanisms elucidated through nested association mapping and near-isogenic line analysis

Gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is one of the most important diseases of maize worldwide. The pathogen has a necrotrophic lifestyle and no major genes are known for GLS. Quantitative resistance, although poorly understood, is important for GLS management. We used genetic mapping to refine understanding of the genetic architecture of GLS resistance and to develop hypotheses regarding the mechanisms underlying quantitative disease resistance (QDR) loci. Nested association mapping (NAM) was used to identify 16 quantitative trait loci (QTL) for QDR to GLS, including seven novel QTL, each of which demonstrated allelic series with significant effects above and below the magnitude of the B73 reference allele. Alleles at three QTL, qGLS1.04, qGLS2.09, and qGLS4.05, conferred disease reductions of greater than 10%. Interactions between loci were detected for three pairs of loci, including an interaction between iqGLS4.05 and qGLS7.03. Near-isogenic lines (NILs) were developed to confirm and fine-map three of the 16 QTL, and to develop hypotheses regarding mechanisms of resistance. qGLS1.04 was fine-mapped from an interval of 27.0 Mb to two intervals of 6.5 Mb and 5.2 Mb, consistent with the hypothesis that multiple genes underlie highly significant QTL identified by NAM. qGLS2.09, which was also associated with maturity (days to anthesis) and with resistance to southern leaf blight, was narrowed to a 4-Mb interval. The distance between major leaf veins was strongly associated with resistance to GLS at qGLS4.05. NILs for qGLS1.04 were treated with the C. zeae-maydis toxin cercosporin to test the role of host-specific toxin in QDR. Cercosporin exposure increased expression of a putative flavin-monooxygenase (FMO) gene, a candidate detoxification-related gene underlying qGLS1.04. This integrated approach to confirming QTL and characterizing the potential underlying mechanisms advances the understanding of QDR and will facilitate the development of resistant varieties.

High-resolution mapping and characterization of qRgls2, a major quantitative trait locus involved in maize resistance to gray leaf spot

BACKGROUND

Gray leaf spot (GLS) caused by Cercospora zeae-maydis (Czm) or Cercospora zeina (Cz) is a devastating maize disease and results in substantial yield reductions worldwide. GLS resistance is a quantitatively inherited trait. The development and cultivation of GLS-resistant maize hybrids are the most cost-effective and efficient ways to control this disease.

RESULTS

We previously detected a major GLS resistance QTL, qRgls2, in bin 5.03-04, which spans the whole centromere of chromosome 5 encompassing a physical distance of ~110-Mb. With advanced backcross populations derived from the cross between the resistant Y32 and susceptible Q11 inbred lines, a sequential recombinant-derived progeny testing strategy was adapted to fine map qRgls2. We narrowed the region of qRgls2 from an initial ~110-Mb to an interval of ~1-Mb, flanked by the markers G346 and DD11. qRgls2 showed predominantly additive genetic effects and significantly increased the resistance percentage by 20.6 to 24.6% across multiple generations. A total of 15 genes were predicted in the mapped region according to the 5b.60 annotation of the maize B73 genome v2. Two pieces of the mapped qRgls2 region shared collinearity with two distant segments on maize chromosome 4.

CONCLUSIONS

qRgls2, a major QTL involved in GLS resistance, was mapped to a ~1-Mb region close to the centromere of chromosome 5. There are 15 predicted genes in the mapped region. It is assumed that qRgls2 could be widely used to improve maize resistance to GLS.

Unraveling genomic complexity at a quantitative disease resistance locus in maize

Multiple disease resistance has important implications for plant fitness, given the selection pressure that many pathogens exert directly on natural plant populations and indirectly via crop improvement programs. Evidence of a locus conditioning resistance to multiple pathogens was found in bin 1.06 of the maize genome with the allele from inbred line "Tx303" conditioning quantitative resistance to northern leaf blight (NLB) and qualitative resistance to Stewart's wilt. To dissect the genetic basis of resistance in this region and to refine candidate gene hypotheses, we mapped resistance to the two diseases. Both resistance phenotypes were localized to overlapping regions, with the Stewart's wilt interval refined to a 95.9-kb segment containing three genes and the NLB interval to a 3.60-Mb segment containing 117 genes. Regions of the introgression showed little to no recombination, suggesting structural differences between the inbred lines Tx303 and "B73," the parents of the fine-mapping population. We examined copy number variation across the region using next-generation sequencing data, and found large variation in read depth in Tx303 across the region relative to the reference genome of B73. In the fine-mapping region, association mapping for NLB implicated candidate genes, including a putative zinc finger and pan1. We tested mutant alleles and found that pan1 is a susceptibility gene for NLB and Stewart's wilt. Our data strongly suggest that structural variation plays an important role in resistance conditioned by this region, and pan1, a gene conditioning susceptibility for NLB, may underlie the QTL.

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina

BACKGROUND

Gray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C. zeina limits production of this staple food crop.

RESULTS

A maize RIL population (F7:S6) from a cross between CML444 and SC Malawi was field-tested under GLS disease pressure at five field sites over three seasons in KwaZulu-Natal, South Africa. Thirty QTL identified from eleven field trials (environments) were consolidated to seven QTL for GLS resistance based on their expression in at least two environments and location in the same core maize bins. Four GLS resistance alleles were derived from the more resistant parent CML444 (bin 1.10, 4.08, 9.04/9.05, 10.06/10.07), whereas the remainder were from SC Malawi (bin 6.06/6.07, 7.02/7.03, 9.06). QTLs in bin 4.08 and bin 6.06/6.07 were also detected as joint QTLs, each explained more than 11% of the phenotypic variation, and were identified in four and seven environments, respectively. Common markers were used to allocate GLS QTL from eleven previous studies to bins on the IBM2005 map, and GLS QTL "hotspots" were noted. Bin 4.08 and 7.02/7.03 GLS QTL from this study overlapped with hotspots, whereas the bin 6.06/6.07 and bin 9.06 QTLs appeared to be unique. QTL for flowering time (bin 1.07, 4.09) in this population did not correspond to QTL for GLS resistance.

CONCLUSIONS

QTL mapping of a RIL population from the subtropical maize parents CML444 and SC Malawi identified seven QTL for resistance to gray leaf spot disease caused by C. zeina. These QTL together with QTL from eleven studies were allocated to bins on the IBM2005 map to provide a basis for comparison. Hotspots of GLS QTL were identified on chromosomes one, two, four, five and seven, with QTL in the current study overlapping with two of these. Two QTL from this study did not overlap with previously reported QTL.